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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Safe food for infants: An EU-China project to enhance the control of safety risks raised by microbial and chemical hazards all along the infant food chains

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Global Pediatrics 2022年 2卷

作者： Engel, Erwan Rivière, Gilles Kemmer, Diana Deusch, Oliver Fuchsbauer, Norbert Biesterveld, Steven Krystalli, Evangelia Bondoux, Marion Li, Guang Yang, Weikang Hou, Jianbo Liang, Ying Yang, Hua Fang, Weihuan Pettoello-Mantovani, Massimo Flynn, Brian Rantsiou, Kalliopi Van der Burg, Bart Bover-Cid, Sara Zwietering, Marcel H. French National Research Institute for Agriculture Food and Environment (INRAE) UR QuaPA MASS Group Saint-Genès-Champanelle France French Agency for Food Environmental and Occupational Health & Safety (ANSES) Maisons-Alfort France Fraunhofer Institute for Process Engineering and Packaging (IVV) Freising Germany Computomics GmbH Tübingen Germany HiPP-Werk Georg Hipp OHG Pfaffenhofen Germany Friesland Campina Nederland BV Amersfoort Netherlands Yiotis Anonimos Emporiki & Viomixaniki Etaireia Athens Greece INRAE Transfert Clermont-Ferrand France Beingmate (Hangzhou) Food Research Institute Co. Ltd Hangzhou China Yangzhou Fangguang Food Co. Ltd. Yangzhou China Zhejiang Academy of Science & Technology for Inspection & Quarantine (ZAIQ Hangzhou China Jiangsu Academy of Agricultural Sciences (JAAS) Nanjing China Zhejiang Academy of Agricultural Sciences (ZAAS) Hangzhou China Zhejiang University (ZJU) Hangzhou China EPA-UNEPSA Berlin Germany Creme software LTD (Creme Global) Dublin Ireland University of Turin Department of Agricultural Forest and Food Sciences Turin Italy BioDetection Systems B.V. Amsterdam Netherlands Institut de Recerca i Tecnologia Agroalimentàries (IRTA) Food Safety and Functionality Program Monells Spain Wageningen University & Research Food Microbiology Wageningen Netherlands

The EU-project SAFFI targets food for EU's 15 million and China's 45 million children under the age of three. It aims at developing an integrated approach to enhance the identification, assessment, detection and mitigation of health risks raised by microbial and chemical hazards along EU and China infant food chains. SAFFI will benchmark the main risks through an extensive hazard identification system based on multiple data sources and a risk ranking procedure. It will also develop procedures to enhance top-down and bottom-up hazard control by combining management options with a panel of technologies for the detection and mitigation of priority hazards. Furthermore, it will explore unexpected contaminants by predictive toxicology and improve risk-based food safety management of biohazards by omics and predictive microbiology. SAFFI will co-develop with and deliver to stakeholders a decision-support system (DSS) to enhance safety control all along the food chain. This DSS will integrate the databases, procedures and methods described above and will be a framework for a generic DSS dedicated to other food. This overall methodology will also be implemented in a complementary Chinese side of the project, and exemplified for each side, with four case studies that were selected to cover priority hazards, main ingredients, processes and control steps of the infant food chain. Resulting databases, tools and procedures will be shared, cross-validated, concatenated, benchmarked and finally harmonized for further use in the EU and China. This EU-China multi-actor consortium of 20 partners involves academia, food safety authorities, infant food companies, a paediatrics association and technological and data-science SMEs. © 2022

关键词： Baby food Chemical contaminants Decision support system Food safety Foodborne hazards Hazard control Hazard detection Risk assessment

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How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

arXiv

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arXiv 2023年

作者： Bosoni, Emanuele Beal, Louis Bercx, Marnik Blaha, Peter Blügel, Stefan Bröder, Jens Callsen, Martin Cottenier, Stefaan Degomme, Augustin Dikan, Vladimir Eimre, Kristjan Flage-Larsen, Espen Fornari, Marco Garcia, Alberto Genovese, Luigi Giantomassi, Matteo Huber, Sebastiaan P. Janssen, Henning Kastlunger, Georg Krack, Matthias Kresse, Georg Kühne, Thomas D. Lejaeghere, Kurt Madsen, Georg K.H. Marsman, Martijn Marzari, Nicola Michalicek, Gregor Mirhosseini, Hossein Müller, Tiziano M.A. Petretto, Guido Pickard, Chris J. Poncé, Samuel Rignanese, Gian-Marco Rubel, Oleg Ruh, Thomas Sluydts, Michael Vanpoucke, Danny E.P. Vijay, Sudarshan Wolloch, Michael Wortmann, Daniel Yakutovich, Aliaksandr V. Yu, Jusong Zadoks, Austin Zhu, Bonan Pizzi, Giovanni Institut de Ciència de Materials de Barcelona ICMAB-CSIC Campus UAB Bellaterra08193 Spain Univ. Grenoble-Alpes CEA IRIG-MEM-L Sim Grenoble38000 France LausanneCH-1015 Switzerland Institute for Materials Chemistry Technical University of Vienna Getreidemarkt 9/165-TC ViennaA-1060 Austria Peter Grünberg Institut Institute for Advanced Simulation Forschungszentrum Jülich JARA JülichD-52425 Germany Forschungszentrum Jülich JülichD-52425 Germany Department of Electromechanical Systems and Metal Engineering Ghent University Belgium Ghent University Belgium Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan Norwegian EuroHPC Competence Center Sigma2 AS Norway SINTEF Industry Materials Physics Oslo Norway Department of Physics Science of Advanced Materials Program Central Michigan University Mount PleasantMI48859 United States Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium LausanneCH-1015 Switzerland Kongens Lyngby2800 Denmark VilligenCH-5232 Switzerland University of Vienna Faculty of Physics Center for Computational Materials Science Kolingasse 14-16 ViennaA-1090 Austria VASP Software GmbH Sensengasse 8 ViennaA-1090 Austria Helmholtz-Zentrum Dresden-Rossendorf GörlitzD-02826 Germany Center for Sustainable Systems Design University of Paderborn PaderbornD-33098 Germany OCAS NV ArcelorMittal Global R&D Gent Pres. J. F. Kennedylaan 3 ZelzateB-9060 Belgium Dynamics of Condensed Matter Theoretical Chemistry University of Paderborn PaderbornD-33098 Germany HPE HPC EMEA Research Lab BaselCH-4051 Switzerland Department of Materials Science & Metallurgy University of Cambridge 27 Charles Babbage Road CambridgeCB3 0FS United Kingdom Advanced Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba Sendai980-8577 Japan Department of Materials Science and Engineering McMaster University 1280 Main Street West HamiltonONL8S 4L8 Canada ePot

In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies). © 2023, CC BY.

关键词： Density functional theory

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Formalizing Atom-typing and the Dissemination of Force Fields with Foyer

arXiv

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arXiv 2018年

作者： Klein, Christoph Summers, Andrew Z. Thompson, Matthew W. Gilmer, Justin McCabe, Clare Cummings, Peter T. Sallai, Janos Iacovella, Christopher R. Department of Chemical and Biomolecular Engineering Vanderbilt University NashvilleTN37235 United States Center Vanderbilt University NashvilleTN37235 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37235 United States Department of Chemistry Vanderbilt University NashvilleTN37235 United States Institute for Software Integrated Systems Vanderbilt University NashvilleTN37235 United States

A key component to enhancing reproducibility in the molecular simulation community is reducing ambiguity in the parameterization of molecular models. Ambiguity in molecular models often stems from the dissemination of molecular force fields in a format that is not directly usable or is ambiguously documented via a non-machine readable mechanism. Specifically, the lack of a general tool for performing automated atom-typing under the rules of a particular force field facilitates errors in model parameterization that may go unnoticed if other researchers are unable reproduce this process. Here, we present Foyer, a Python tool that enables users to define force field atom-typing rules in a format that is both machine- and human-readable thus eliminating ambiguity in atom-typing and additionally providing a framework for force field dissemination. Foyer defines force fields in an XML format, where SMARTS strings are used to define the chemical context of a particular atom type. Herein we describe the underlying methodology of the Foyer package, highlighting its advantages over typical atom-typing approaches and demonstrate is application in several use-cases. Copyright © 2018, The Authors. All rights reserved.

关键词： Atoms

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Recent Advances in systems and Network Medicine: Meeting Report from the First International Conference in systems and Network Medicine

Recent Advances in Systems and Network Medicine: Meeting Rep...

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作者： Kurnat-Thoma, Emma Baranova, Ancha Baird, Pat Brodsky, Elia Butte, Atul J. Cheema, Amrita K. Cheng, Feixiong Dutta, Shuchismita Grant, Christina Giordano, James Maitland-Van Der Zee, Anke H. Fridsma, Douglas B. Jarrin, Robert Kann, Maricel G. Keeney, Jonathon Loscalzo, Joseph Madhavan, Guru Maron, Bradley A. Mcbride, Dennis K. Mckean, Maeve Mun, Seong K. Palmer, James C. Patel, Bakul Parakh, Kapil Pariser, Anne R. Pristipino, Christian Radstake, Timothy R.D.J. Rajasimha, Harsha K. Rouse, William B. Rozman, Damjana Saleh, Alif Schmidt, Harald H.H.W. Schultz, Nikolaus Sethi, Tavpritesh Silverman, Edwin K. Skopac, Jessica Svab, Igor Trujillo, Sylvia Valentine, James E. Verma, Dinesh West, Bruce J. Vasudevan, Sona BethesdaMD United States Genetics and Genomics Georgetown University School of Nursing and Health Studies WashingtonDC United States School of Systems Biology George Mason University FairfaxVA United States Global Software Standards Philips Pleasant PrairieWI United States Pine Biotech New OrleansLA United States San FranciscoCA United States Department of Biochemistry Molecular and Cellular Biology Georgetown University Medical Center WashingtonDC United States Cleveland Clinic Lerner College of Medicine Case Western Reserve University Cleveland Clinic ClevelandOH United States Institute for Quantitative Biomedicine Rutgers University The State University of New Jersey PiscatawayNJ United States Rare Disease Institute Division of Genetics and Metabolism Children's National Medical Center WashingtonDC United States Department of Neurology Neuroethics Studies Program-Pellegrino Center for Clinical Bioethics O'Neill-Pellegrino Program in Brain Sciences and Global Law and Policy Georgetown University Medical Center WashingtonDC United States Department of Biochemistry Neuroethics Studies Program-Pellegrino Center for Clinical Bioethics O'Neill-Pellegrino Program in Brain Sciences and Global Law and Policy Georgetown University Medical Center WashingtonDC United States Department of Respiratory Medicine Amsterdam University Medical Centers University of Amsterdam Amsterdam Netherlands American Medical Informatics Association WashingtonDC United States Department of Biological Sciences University of Maryland Baltimore County BaltimoreMD United States Department of Biochemistry and Molecular Medicine George Washington University WashingtonDC United States Department of Medicine Brigham and Women's Hospital Harvard Medical School BostonMA United States National Academy of Engineering The National Academies of Sciences Engineering and Medicine WashingtonDC United States WashingtonDC United States Georgetown University Global Health

The First International Conference in systems and Network Medicine gathered together 200 global thought leaders, scientists, clinicians, academicians, industry and government experts, medical and graduate students, postdoctoral scholars and policymakers. Held at Georgetown University Conference Center in Washington D.C. on September 11-13, 2019, the event featured a day of pre-conference lectures and hands-on bioinformatic computational workshops followed by two days of deep and diverse scientific talks, panel discussions with eminent thought leaders, and scientific poster presentations. Topics ranged from: systems and Network Medicine in Clinical Practice;the role of -omics technologies in Health Care;the role of Education and Ethics in Clinical Practice, systems Thinking, and Rare Diseases;and the role of Artificial Intelligence in Medicine. The conference served as a unique nexus for interdisciplinary discovery and dialogue and fostered formation of new insights and possibilities for health care systems advances. © Emma Kurnat-Thoma et al. 2020 Published by Mary Ann Liebert, Inc. 2020.

关键词： Artificial intelligence

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Enhancing verification and validation education using active learning tools developed through an academia-industry partnership 123

Enhancing verification and validation education using active...

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123rd ASEE Annual Conference and Exposition

作者： Acharya, Sushil Manohar, Priya Schilling, Walter W. Wu, Peter Y. Robert Morris University PittsburghPA United States Software Engineering Program Milwaukee School of Engineering MilwaukeeWI United States Department of Computer and Information Systems Robert Morris University United States

Imparting real world experiences in a software verification and validation (SV&V) course is often a challenge due to the lack of effective active learning tools. This pedagogical requirement is important because graduates are expected to develop software that meets rigorous quality standards in functional and application domains. Realizing the necessity of such teaching tools, the authors designed and developed eighteen (18) delivery hours of Case Studies, sixteen (16) delivery hours of Class Exercises, and six (6) delivery hours of Video Case Studies for use in courses that impart knowledge on SV&V topics viz. requirements engineering, software reviews, configuration management, and software testing. Four key skill areas sought after by employers, namely communication skills, applied knowledge of methods, applied knowledge of tools, and research exposure are used to drive the development funded by a National Science Foundation grant and perfected through an industry-academia partnership. In this paper, we discuss in detail the four project plans the researchers and their industry counterparts followed over the past two years in the development and eventual dissemination of active learning tools. A course enhancement plan was used to drive activities related to reviewing, enhancing, and modularizing modules, identified by a gap analysis performed by focus groups comprised of industry and academic partners. The course delivery plan was used to drive activities related to developing content delivery strategies. An evaluation and assessment plan was used to drive activities related to periodically evaluating student learning and assessing the project. And finally a course dissemination plan is being used to drive activities related to disseminating course modules and assessment reports. Active learning tools have been disseminated through a workshop and other means to universities and industry partners. © American Society for engineering Education, 2016.

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Development of a cognitive vehicle system for simulation of driving behavior

Development of a cognitive vehicle system for simulation of ...

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IEEE International Conference on Cognitive Informatics

作者： Marvin T. Chan Christine Chan Craig Gelowitz Software Systems Engineering Program University of Regina Regina SK Canada

ISBN: (纸本)9781509038473

This paper presents Racer, a car-racing simulator where the human player races a car against three game-controlled cars in a three-dimensional environment. The game incorporates artificial intelligence (AI) techniques, and the objective of AI in video games is not to defeat the human player, but to provide the player with a challenging and enjoyable experience. The game is a software simulation that incorporates considerations of human driving behavior. The paper provides a brief history of AI techniques in games, presents the use of AI techniques in contemporary video games, and discusses the contemporary video game AI techniques that were implemented in the development of Racer.

关键词： Games Automobiles Artificial intelligence Engines Monitoring software systems

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Guest editorial: The 2016 capstone design conference

Guest editorial: The 2016 capstone design conference

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作者： Brackin, Patsy Howe, Susannah Rogers, Peter Stanfill, R. Keith Beyerlein, Steven Kanai, Junichi Vallino, Jim Palo, Scott Department of Mechanical Engineering Rose-Hulman Institute of Technology 5500 Wabash Avenue CM 165 Terre HauteIN47803 United States Picker Engineering Program Smith College 151 Ford Hall NorthamptonMA01063 United States Department of Engineering Education Ohio State University 3070 Smith Laboratory 174 W. 18th Avenue ColumbusOH43210 United States Engineering Innovation Institute University of Florida P.O. Box 116000 GainesvilleFL32611-6000 United States Department of Mechanical Engineering University of Idaho 875 Perimeter Drive MoscowID83844-0902 United States Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY United States Department of Software Engineering Rochester Institute of Technology 134 Lomb Memorial Drive RochesterNY14623-5608 United States Department of Aerospace Engineering Sciences University of Colorado 429 UCB BoulderCO80309 United States

The goal of the 2016 Capstone Design Conference held in Columbus, OH was to build upon the success of previous conferences (2007 and 2010 in Boulder, CO, 2012 in Champaign, IL, and 2014 in Columbus, OH) and expand the community of educators, students, and industry members engaged in discussing, analyzing, and improving capstone design education. Sessions at the 2016 Capstone Design Conference were designed for vibrant sharing of ideas and experiences across the capstone community via interactive panel sessions, poster session socials, hands-on workshops, and other formal and informal networking activities. This editorial discusses conference planning, structure, and feedback. Technical papers that follow in this issue document scholarship surrounding noteworthy capstone course innovations. Most of these began as four page peer-reviewed papers included in the conference proceedings. © 2017 TEMPUS Publications.

关键词： Teaching

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A framework of Thailand higher education dashboard system

A framework of Thailand higher education dashboard system

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International Computer Science and engineering Conference (ICSEC)

作者： Nuansri Denwattana Apisit Saengsai Software engineering program Burapha University Chonburi THAILAND Information Systems Engineering Research Laboratory Faculty of Informatics Burapha University Chonburi THAILAND

Prominent organizations, currently, have analytical data-driven tool to support their decision making. A chart-like dashboard is the most appropriate tool to make integrated decisions encompassing multiple functions based on relevance information systems. Such tools, however, are commonly used in commercial firms rather than in the public organizations, especially in the education sections. It is crucial that several missions for the higher education in Thailand, such as graduate performance, research study, academic services to the society, and art & culture preservation, need a decision supporting tool to accomplish such goals. In this paper, we propose the dashboard framework for Higher Education, called TheDB (Thailand higher education DashBoard). It is generally very challenging for the higher education to have their own dashboards for different levels in the organization. We have implemented TheDB framework in nursing colleges of Public Health Ministry. In addition, they explicit their work operation via the dashboard for education quality assurance audited and approved by both related authorize organizations, including Thailand Nursing Council.

关键词： Information systems Education Organizations Medical services Quality assurance Decision support systems

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Case study based educational tools for teaching software V&V course at undergraduate level 122

Case study based educational tools for teaching software V&V...

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2015 122nd ASEE Annual Conference and Exposition

作者： Manohar, Priya Acharya, Sushil Wu, Peter Y. Ansari, Ali A. Schilling, Walter W. Robert Morris University PittsburghPA United States Department of Computer and Information Systems Robert Morris University United States Virginia State University United States Software Engineering Program Milwaukee School of Engineering MilwaukeeWI United States

One of the critical problems facing software industry today is the lack of appreciation of the full benefits that can be derived from software Verification and Validation (V&V) and an associated problem of shortage of adequately trained V&V practitioners. To address this situation, software V&V course curriculum is being improved at author's institution via a NSF-funded project. The basic objectives of this project are to improve software education to make it well aligned with academic research as well as industry best practices. In addition, it is aimed that the course material could also be used to enhance on-the-job professional training in SW industry settings, thereby helping to increase the pool of professionals with contemporary V&V knowledge and skills. The new course curriculum enhancement described in this paper is guided by academic research and industry best practices that focus on four specific V&V focus areas: requirements engineering, reviews, configuration management, and testing. Among many educational tools that are being developed to achieve project objectives, the work related to the development of case studies is described here. Historically, case studies have been as educational tools in business, law and medicine but not so much in software engineering. The hypothesis is that case studies would be effective educational tools to introduce real-world professional practices into the classroom which would help the students in identifying and solving problems, and develop a perspective on knowledge application. In this paper we describe a set of V&V related casestudies that we have drawn from industry experiences and developed them as pedagogical tools. These case-studies cover several important topics in S/W V&V domain such as software testing, legal issues in software, software consumer protection, and requirements from the customers' perspectives. We will also report on the results of initial implementation of case studies related to software te

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